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Drive a 7-axis robot arm with natural language

OpenClaw is taught a skill and rules for the NERO arm, then writes and runs Python control scripts from plain-language movement requests.

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Use case overview

OpenClaw is taught a skill and rules for the NERO arm, then writes and runs Python control scripts from plain-language movement requests.

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Reported experience

  1. What they did

    After installing OpenClaw (the article suggests the Qwen model), the author adds a skill folder holding a skill file and an API reference for the pyAgxArm SDK. These set rules for connecting over CAN, enabling the arm before switching modes, units, and waiting for each motion to finish. OpenClaw then generates Python scripts from plain-language movement requests.

  2. How it went

    The article is a setup walkthrough and a demo video link. It reports no measured results, success rates, or example prompts with outputs.

  3. Worth knowing

    The skill only generates code. You must set up CAN, install pyAgxArm and power the arm yourself, and the skill advises clearing the workspace and testing with small, slow moves first.

Example prompts

Try with OpenClaw
I have a [robot arm model] with an SDK at [SDK docs link or path]. Read the docs and write a skill file with the safety rules: [joint limits, speed cap, workspace bounds]. Then, when I ask for a movement in plain language, write a Python script to do it and show me the script before running it on the arm. Finish when you can complete [simple test move, e.g. move to home position and back] safely.

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